For SaaS teams hiring AI talent
AI and Machine Learning Hiring FAQ: Roles, Costs and Who to Hire First
Short, direct answers to the questions US SaaS teams ask before they hire AI and machine learning engineers: what each role does, what it costs in the US and in Latin America, and which one to hire first. The answers draw on LatamCent's own salary data and the recruiters who place AI and ML engineers from Latin America with US companies.
- Hires made in 21 days or less
- 30+ AI/ML specialties
- Engineers who work US hours
Are AI Engineers in Demand?
Yes, AI engineers are in high demand. AI engineer is the fastest-growing job title in the US on LinkedIn's 2026 list. At LatamCent, half of the new engineering roles we recruited for between May and October 2026 were AI roles,…
Is MLOps Harder Than DevOps?
Yes, MLOps is harder than DevOps for most engineers, because it covers everything DevOps does plus data and models. A DevOps engineer keeps code shipping and systems running. An MLOps engineer also versions data, retrains models and catches models that…
What’s the Difference Between a Data Engineer and a Machine Learning Engineer?
The main difference between a data engineer and a machine learning engineer is what they deliver. A data engineer builds the pipelines that collect, clean and store your data. A machine learning engineer uses that data to build models that…
What’s the Difference Between an AI Engineer and a Machine Learning Engineer?
The main difference between an AI engineer and a machine learning engineer is where they start. An AI engineer builds product features on top of existing models, such as large language models (LLMs). A machine learning engineer designs, trains and…
Didn't find your question?
Tell us the AI or ML role you're hiring for. We'll walk you through salaries, time zones and what to screen for, then send pre-vetted Latin American engineers who work your hours. Most roles are filled in 21 days or less.
